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Dapper Labs: Minting NFTs on Flow takes less energy than a Google Search

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Dapper Labs said that minting nonfungible tokens (NFTs) on Flow takes less energy than a Google Search or an Instagram post. Deloitte Canada confirmed that.

These findings are interesting considering all of the myths and realities floating around about NFTs, which some people view as either the savior of gaming or a scammy monetization scheme.

Dapper Labs said that operating the Flow blockchain requires just 0.18 gigawatt hours (GWh) of energy, based on 2021 usage. Dapper Labs created the Flow blockchain protocol to support its creation of NFTs for NBA Top Shot, which are unique collectible videos that basketball fans can own.

Dapper Labs acknowledged that it’s no secret that many people believe that Proof of Work blockchains, like Bitcoin and Ethereum, are bad for the environment. But it contends that Flow doesn’t use nearly as much energy. Dapper Labs uses something different with Flow, dubbed Proof of Stake.


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Proof of Work solves huge cryptographic puzzles to reach consensus, or an agreement that the records of the digital ledger of the blockchain are correct. It requires a ton of energy to complete these operations.

Blockchain games utilize proof-of-stake blockchains like Solana, Avalanche, Hedera, Polygon, and Immutable X. Proof of Stake doesn’t take much more energy than cloud-based services.

Flow uses just 0.18 (gigawatt hours) GWh annually, based on 2021 usage. That means that minting an NFT on Flow takes less energy than a Google search or Instagram post.

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And how does this stack up to other Web3 platforms? Based on publicly available data — across a variety of sources — Dapper and Deloitte Canada found: Bitcoin uses 178,040 GWh per year, Ethereum uses 108,390, Solana uses 11.05, Polygon uses 0.79, and Flow comes in at the aforementioned 0.18.

“At Deloitte, we are always interested in examining what’s next, and when we were approached to create an objective and comprehensive energy consumption review for Flow in 2021, we knew this was the exact challenge we were interested in tackling,” said Nathan Steeghs, partner and national climate lead at Deloitte Canada, in a statement. “Based on our analysis and survey of the network, we discovered Flow uses significantly less energy than reported by other protocols. This is attributed to Flow operating on a Proof of Stake consensus system versus Proof of Work which is generally more energy and carbon intensive.”

In addition to operating on a Proof of Stake consensus system, Flow’s unique multi-role node architecture securely divides the processing between specialized node types, making the network significantly more efficient than other blockchain architectures. And because of this architecture, the overall energy use of the network won’t increase significantly even if the activity increases by 100 times or more, making the per-transaction energy footprint decrease over time, Dapper Labs said.

The primary drivers of the energy usage are collection and consensus nodes. These nodes perform less intensive work than execution nodes but have a larger population resulting in higher consumption. In addition, the seven execution nodes only require seven machines, reducing the impact of the baseline 60 watts of power from additional hardware.

Deloitte Canada’s assessment focused on Flow’s blockchain 2021 electricity consumption for node operations (execution, consensus, collection and verification nodes), and thus related Scope 2 emissions drawing on the Greenhouse Gas (GHG) Protocol.

To estimate energy and emissions, Deloitte Canada surveyed node operators and received data for 90% of the node population. Energy consumption and GHG emissions data are subject to inherent limitations of accuracy given the nature and the methods used for determining such data.

The selection of different acceptable measurement techniques can result in materially different measurements due to varying precision of different techniques. To this regard, Deloitte obtained relevant equipment and node operational information from the survey to estimate the energy consumption by each node type, and then extrapolated the energy consumption for 10% of the remaining nodes considering relevant quantification guidance for GHG emissions reporting per the GHG Protocol.

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